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A systematic literature review of factors influencing the adoption of climate-smart agricultural practices
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A systematic literature review of factors influencing the adoption of climate-smart agricultural practices
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A systematic literature review of factors influencing the adoption of climate-smart agricultural practices
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Journal Article
A systematic literature review of factors influencing the adoption of climate-smart agricultural practices
2024
Overview
Adopting climate-smart agricultural (CSA) practices is a long-term solution for enhancing agricultural sustainability and food security under the changing climate. However, the penetration rate of CSA practices remains low worldwide. Understanding the key factors driving the adoption of CSA practices is key to increasing its penetration. This study provides a systematic review of the literature comprising 190 studies published between 2013 and 2023. Based on the reviewed literature, we provide comprehensive definitions of CSA practices from broad and narrow perspectives. We also discuss the factors influencing farmers’ decisions to adopt CSA practices from four categories: socio-demographic factors, institutional factors, resource endowment factors, and socio-economic factors. Our literature review reveals that most of the factors (e.g., age, gender, education, risk perception and preference, access to credit, farm size, production conditions, off-farm income, and labor allocation) discussed in the literature have a dual (either positive or negative) impact on CSA practice adoption. The variables such as labor endowment, land tenure security, access to extension services, access to agricultural training, membership in farmers’ organizations, non-governmental organization (NGO) support, climate conditions, and access to information consistently and positively impact CSA practice adoption. These findings provide solid evidence for designing appropriate policy instruments that help accelerate CSA diffusion and transmission. We also find gaps in CSA practice measurements, influencing factor identification, and econometric methods used for empirical analysis, which should be explored by future research.
